Meta's AI Training and Inference Infrastructure is growing exponentially to support ever increasing use cases of AI. This results in a dramatic scaling challenges that our engineers have to deal with on a daily basis. We need to build and evolve our network infrastructure and the related software that connects myriad of training accelerators like GPUs together. In addition, we need to ensure that the system is running smoothly and meets stringent performance and availability requirements of large-scale training and inference workloads. To improve performance of these systems we constantly look for opportunities across stack: network fabric, host networking, communication libraries and scheduling infrastructure.
Sr. Technical Lead Manager - AI/HPC Systems Performance Responsibilities:
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- Support multi-disciplinary team of engineers focused on monitoring, benchmarking and looking for opportunities to improve performance of AI Training and Inference.
- Be a subject matter expert in the performance of AI Training and Inference domain. With special emphasis on collectives, scale-up/scale-out network and host networking.
- Lead teams that deliver on multiple projects of increasing dependencies in an ambiguous or high-impact area.
- Help define technical vision and strategy for the organization. Drive multi-year roadmaps to make progress towards the related objectives.
- Work with cross functional teams and provide guidance on the AI network architecture including topologies, transport, congestion control techniques.
- Experience with collective libraries or networking technologies related to RoCE or InfiniBand.
- 10+ years of experience in designing, developing and operating high performance software and hardware systems.
- Experience in building systems that simplify triaging performance issues in complex scale-out distributed applications.
- Demonstrated experience recruiting and managing technical teams, including performance management.
- 5+ years experience in managing manager and Sr. technical leads.
- BA/BS in Computer Science (In lieu of degree, 4+ years work experience).
- Experience with developing communication libraries, such as MPI, NCCL, and UCX.
- Understanding of AI training workloads and demands they exert on networks.
- Understanding of RDMA congestion control mechanisms on IB and RoCE Networks.
- Understanding of the latest artificial intelligence (AI) technologies.
- Experience with machine learning frameworks such as PyTorch and TensorFlow.
- Experience in developing systems software in languages like C++
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$213,000/year to $293,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.